Machine learning models combining computed tomography semantic features and selected clinical variables for accurate prediction of the pathological grade of bladder cancer

OBJECTIVE: The purpose of this research was to develop a radiomics model that combines several clinical features for preoperative prediction of the pathological grade of bladder cancer (BCa) using non-enhanced computed tomography (NE-CT) scanning images. MATERIALS AND METHODS: The computed tomograph...

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Detalles Bibliográficos
Autores principales: Deng, Zhikang, Dong, Wentao, Xiong, Situ, Jin, Di, Zhou, Hongzhang, Zhang, Ling, Xie, LiHan, Deng, Yaohong, Xu, Rong, Fan, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200894/
https://www.ncbi.nlm.nih.gov/pubmed/37223680
http://dx.doi.org/10.3389/fonc.2023.1166245

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200894/
https://www.ncbi.nlm.nih.gov/pubmed/37223680
http://dx.doi.org/10.3389/fonc.2023.1166245

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